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Packages that use NotTrainedException | |
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de.jstacs.classifier | This package provides the framework for any classifier. |
de.jstacs.classifier.scoringFunctionBased | Provides the classes for Classifier s that are based on ScoringFunction s. |
de.jstacs.models | Provides the interface Model and its abstract implementation AbstractModel , which is the super class of all other models. |
de.jstacs.models.discrete | |
de.jstacs.models.discrete.homogeneous | |
de.jstacs.models.discrete.inhomogeneous | This package contains various inhomogeneous models. |
de.jstacs.models.discrete.inhomogeneous.shared | |
de.jstacs.models.mixture | This package is the super package for any mixture model. |
de.jstacs.models.utils |
Uses of NotTrainedException in de.jstacs.classifier |
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Methods in de.jstacs.classifier that throw NotTrainedException | |
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protected void |
AbstractScoreBasedClassifier.check(Sample s)
This method checks if the given Sample can be used. |
protected void |
AbstractScoreBasedClassifier.check(Sequence seq)
This method checks if the given Sequence can be used. |
protected double |
MappingClassifier.getScore(Sequence seq,
int i,
boolean check)
|
protected abstract double |
AbstractScoreBasedClassifier.getScore(Sequence seq,
int i,
boolean check)
This method returns the score for a given Sequence and a given
class. |
Uses of NotTrainedException in de.jstacs.classifier.scoringFunctionBased |
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Methods in de.jstacs.classifier.scoringFunctionBased that throw NotTrainedException | |
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protected double |
ScoreClassifier.getScore(Sequence seq,
int i,
boolean check)
|
Uses of NotTrainedException in de.jstacs.models |
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Methods in de.jstacs.models that throw NotTrainedException | |
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Sample |
Model.emitSample(int numberOfSequences,
int... seqLength)
This method returns a Sample object containing artificial
sequence(s). |
Sample |
AbstractModel.emitSample(int numberOfSequences,
int... seqLength)
|
double |
NormalizableScoringFunctionModel.getLogProbFor(Sequence sequence,
int startpos,
int endpos)
|
double |
CompositeModel.getLogProbFor(Sequence sequence,
int startpos,
int endpos)
|
double |
Model.getProbFor(Sequence sequence)
Returns the probability of the given sequence given the model. |
double |
AbstractModel.getProbFor(Sequence sequence)
|
double |
Model.getProbFor(Sequence sequence,
int startpos)
Returns the probability of (a part of) the given sequence given the model. |
double |
AbstractModel.getProbFor(Sequence sequence,
int startpos)
|
double |
VariableLengthWrapperModel.getProbFor(Sequence sequence,
int startpos,
int endpos)
|
double |
NormalizableScoringFunctionModel.getProbFor(Sequence sequence,
int startpos,
int endpos)
|
double |
Model.getProbFor(Sequence sequence,
int startpos,
int endpos)
Returns the probability of (a part of) the given sequence given the model. |
double |
CompositeModel.getProbFor(Sequence sequence,
int startpos,
int endpos)
|
Uses of NotTrainedException in de.jstacs.models.discrete |
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Methods in de.jstacs.models.discrete that throw NotTrainedException | |
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protected void |
DiscreteGraphicalModel.check(Sequence sequence,
int startpos,
int endpos)
Checks some conditions on a Sequence . |
Uses of NotTrainedException in de.jstacs.models.discrete.homogeneous |
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Methods in de.jstacs.models.discrete.homogeneous that throw NotTrainedException | |
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protected void |
HomogeneousModel.check(Sequence sequence,
int startpos,
int endpos)
Checks some constraints, these are in general conditions on the AlphabetContainer of a (sub)Sequence
between startpos und endpos . |
Sample |
HomogeneousModel.emitSample(int no,
int... length)
Creates a Sample of a given number of Sequence s from a
trained homogeneous model. |
double |
HomogeneousModel.getLogProbFor(Sequence sequence,
int startpos,
int endpos)
|
double |
HomogeneousModel.getProbFor(Sequence sequence,
int startpos,
int endpos)
|
Uses of NotTrainedException in de.jstacs.models.discrete.inhomogeneous |
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Methods in de.jstacs.models.discrete.inhomogeneous that throw NotTrainedException | |
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protected void |
InhomogeneousDGM.check(Sequence sequence,
int startpos,
int endpos)
|
Sample |
DAGModel.emitSample(int n,
int... lengths)
|
double |
DAGModel.getLogProbFor(Sequence sequence,
int startpos,
int endpos)
|
double |
DAGModel.getProbFor(Sequence sequence,
int startpos,
int endpos)
|
abstract String |
InhomogeneousDGM.getStructure()
Returns a String representation of the underlying graph. |
String |
DAGModel.getStructure()
|
Uses of NotTrainedException in de.jstacs.models.discrete.inhomogeneous.shared |
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Methods in de.jstacs.models.discrete.inhomogeneous.shared that throw NotTrainedException | |
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String |
SharedStructureMixture.getStructure()
Returns a String representation of the structure of the used
models. |
Uses of NotTrainedException in de.jstacs.models.mixture |
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Methods in de.jstacs.models.mixture that throw NotTrainedException | |
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protected Sequence[] |
StrandModel.emitSampleUsingCurrentParameterSet(int n,
int... lengths)
|
double |
AbstractMixtureModel.getScoreForBestRun()
Returns the value of the optimized function from the best run of the last training. |
Uses of NotTrainedException in de.jstacs.models.utils |
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Methods in de.jstacs.models.utils that throw NotTrainedException | |
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static Sample |
DiscreteInhomogenousSampleEmitter.emitSample(Model m,
int n)
This method emits a sample with n |
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